The COSMO-SkyMed (CSK) constellation acquires data from its four SAR X-band satellites in several imaging modes,
providing in particular different view angles. The present work investigates the potential of CSK constellation for ground
elevation measurement through SAR radargrammetry. We selected an area around Parkfield (California), where several
CSK acquisitions are available. We used for radargrammetric processing 2 CSK spotlight image pairs acquired at 1 day
of separation, in Same Side Viewing configuration, with baselines of 350 km. Furthermore, a dataset of 33 spotlight
images were selected to derive height measurements through both persistent scatterers interferometry(PSI) and
interferometric processing of 5 1-day separated pairs included in the dataset. We first predict how the errors in the
geometrical parameters and the correlation level between the images impact on the height accuracy. Then, two DEMs
were derived by processing the radargrammetric CSK pairs. According to the outcomes of the feasibility analysis,
processing parameters were chosen in order to guarantee nominal values of height accuracy within the HRTI Level 3
specifications. The products have a final resolution of 3 m. In order to assess the accuracy of these radargrammetric
DEMs, we used the height values provided by the PSI, and an interferometric DEM derived from the CSK tandem-like
pairs.

State of the art simulations are of great interest when designing a new instrument, studying the imaging mechanisms due
to a given scenario or for inversion algorithm design as they allow to analyze and understand the effects of different
instrument configurations and targets compositions.
In the framework of the studies about a new instruments devoted to the estimation of the ocean surface movements using
Synthetic Aperture Radar along-track interferometry (SAR-ATI) an End-to-End simulator has been developed. The
simulator, built in a high modular way to allow easy integration of different processing-features, deals with all the basic
operations involved in an end to end scenario. This includes the computation of the position and velocity of the platform
(airborne/spaceborne) and the geometric parameters defining the SAR scene, the surface definition, the backscattering
computation, the atmospheric attenuation, the instrument configuration, and the simulation of the transmission/reception
chains and the raw data. In addition, the simulator provides a inSAR processing suit and a sea surface movement
retrieval module.
Up to four beams (each one composed by a monostatic and a bistatic channel) can be activated. Each channel provides
raw data and SLC images with the possibility of choosing between Strip-map and Scansar modes. Moreover, the
software offers the possibility of radiometric sensitivity analysis and error analysis due atmospheric disturbances,
instrument-noise, interferogram phase-noise, platform velocity and attitude variations.
In this paper, the architecture and the capabilities of this simulator will be presented. Meaningful simulation examples
will be shown.

Spaceborne synthetic aperture radars (SARs) operating at X-band and above allow observations of Earth surface at very
high spatial resolution. Moreover, recent polarimetric SARs enable the complete characterization of target scattering and
extinction properties. Nowadays several spaceborne X-band SAR systems are operative, and plans exist for systems
operating at higher frequency bands (i.e. Ku, Ka and W). Although higher frequencies may have interesting and
distinctive applications, atmospheric effects, especially in precipitating conditions, may affect the surface SAR response
in both the signal amplitude and its phase, as assessed by numerous works in the last years. A valid tool to analyze and
characterize the SAR response in these conditions is represented by forward modeling, where a known synthetic
scenario, which is described by user-selected surface and atmospheric conditions, is considered. Thus, the SAR echoes
corresponding to the synthetic scenarios are simulated using electromagnetic models. In this work a 3-D realistic
polarimetric SAR response numerical simulator is presented. The proposed model framework accounts for the SAR slant
observing geometry and it is able to characterize the polarimetric response both in amplitude and phase. In this work we
have considered both X and Ka bands, thus exploring the atmospheric effects for the present and future polarimetric
systems. The atmospheric conditions are simulated using the System for Atmospheric Modeling (SAM) which is an
high-resolution mesoscale model. SAM is used to define the three-dimensional distribution of hydrometeors which are
among the inputs used in the Hydrometeor Ensemble Scattering Simulator (HESS) T-Matrix which allow simulating the
SAR signal due to the atmospheric component. The SAR surface component is, instead, simulated by a Semi Empirical
Model (SEM) for bare-soils conditions and SEAWIND2 two-scale model for ocean surfaces. The proposed methodology
has been applied in this work to assess the sensitivity of the considered frequency bands to different hydrometeor spatial
distributions above some examples surface backgrounds.

This paper provides a proof-of-concept for the use of the new Intermittent Small Baseline Subset (ISBAS) approach to
study ground elevation changes in areas of peat and organic soils in north Wales, which are generally, unfavourable for
conventional C-band interferometric applications. A stack of 53 ERS-1/2 C-band SAR scenes acquired between 1993
and 2000 in descending mode was processed with both the standard low-pass SBAS method and ISBAS. The latter
revealed exceptional improvements in the coverage of ground motion solutions with respect to the standard approach.
The number of identified coherent and intermittently coherent pixels increased by a factor of 26 with respect to the
SBAS solution, and extended the coverage of results across unfavourable land covers, particularly for coniferous
woodland, bog, acid grassland and heather. The greatest increase was achieved over coniferous woodland, which showed
ISBAS/SBAS pixel density ratios above 300. Despite the intermittent nature of the ISBAS solutions, ISBAS provided
velocity standard errors generally below 1-1.5 mm/yr, thus preserving good quality of the estimated ground motion rates.

This second part of the paper about the creation and compilation of the Christchurch, New Zealand, dataset for the detection
of earthquake damages in urban areas deals with the extraction of additional information from the 3D model that can
aid in the detection of destructions. This includes the creation of a height image of the scene, shadow and layover masks
and using a modified version of the SAR simulator CohRaS® to simulate masks of the expected location of specular reflections
in the real TerraSAR-X scene after the earthquake. The algorithms used for the extraction of these data sets and
some ideas for their application for the damage detection task are discussed and first preliminary results are shown.

Nowadays, space-borne Synthetic Aperture Radar (SAR) sensors, can achieve spatial resolutions in the order of 1 m.
However, the exploitation of SAR at very high resolution (VHR) for detecting sparse and isolated damages in urban
areas, caused by earthquakes, is still a challenging task. Within urban settlements, the scattering mechanisms are
extremely complex and simple change detection analyses or classification procedures can hardly be performed. In this
work the 2009, L’Aquila (Italy), earthquake has been considered as case study. Despite about 300 people were killed by
the earthquake, few buildings were completely collapsed, and many others were heavily/partially damaged, resulting in a
quite sparse damage distribution. We have visually analyzed pairs of VHR SAR data acquired by COSMO-SkyMed
satellites, in SPOTLIGHT mode, before and after the earthquake. Such analyses were performed to understand the SAR
response of damaged structures surrounded by unaffected buildings, with the aim to identify possible strategies to map
the damaged buildings by using an automatic classification procedure. The preliminary analyses based on RGB images,
generated by combining pre- and post-event backscattering images, allowed us to figure out how the completely
collapsed and the partially damaged buildings are characterized in the SAR response. These outcomes have been taken
into account to set up a decision tree algorithm (DTA). Decision rules and related thresholds were identified by
statistically analyzing the values of backscattering and derived features. This study point out that many pieces of
information and discrimination rules must be exploited to obtain reliable results when dealing with non-extensive and
sparse damage within a dense urban settlement.

Advanced remote sensing techniques based on space-borne Synthetic Aperture Radar (SAR) have been developed during the last decade showing their applicability for the monitoring of surface displacements in landslide areas. This paper presents an advanced Persistent Scatterer Interferometry (PSI) processing based on the Stable Point Network (SPN) technique, developed by the company Altamira-Information, for the monitoring of an active slowmoving landslide in the mountainous environment of El Portalet, Central Spanish Pyrenees. For this purpose, two TerraSAR-X data sets acquired in ascending mode corresponding to the period from April to November 2011, and from August to November 2013, respectively, are employed. The objective of this work is twofold. On the one hand, the benefits of employing Nonlocal Interferomtric SAR (NL-InSAR) adaptive filtering techniques over vegetated scenarios to maximize the chances of detecting natural distributed scatterers, such as bare or rocky areas, and deterministic point-like scatterers, such as man-made structures or poles, is put forward. In this context, the final PSI displacement maps retrieved with the proposed filtering technique are compared in terms of pixels' density and quality with classical PSI, showing a significant improvement. On the other hand, since SAR systems are only sensitive to detect displacements in the line-of-sight (LOS) direction, the importance of projecting the PSI displacement results retrieved along the steepest gradient of the terrain slope is discussed. The improvements presented in this paper are particularly interesting in these type of applications since they clearly allow to better determine the extension and dynamics of complex landslide phenomena.

This paper examines target models that might be used in simulations of Synthetic Aperture Radar imagery. We
examine the basis for scattering phenomena in SAR, and briefly review the Swerling target model set, before
considering extensions to this set discussed in the literature. Methods for simulating and extracting parameters
for the extended Swerling models are presented. It is shown that in many cases the more elaborate extended
Swerling models can be represented, to a high degree of fidelity, by simpler members of the model set. Further, it
is shown that it is quite unlikely that these extended models would be selected when fitting models to typical
data samples.

The suggested wavelet-based despeckling method for multi-look SAR images does not use any thresholding and
window processing to avoid ringing artifacts, blurring, fusion of edges, etc. Instead, the logical operation of comparison
is applied to wavelet coefficients which are presented in spatial oriented trees (SOTs) of wavelet decomposition
calculated for one and the same region of the earth surface during SAR spacecraft flight. Fusion of SAR images is
decided by keeping the smallest wavelet coefficients from different SOTs in high frequency subbands (details). The
wavelet coefficients related to the low frequency subband (approximation) are processed by another special logical
operation providing with a good smoothing. It is because the described procedure depends on properties of the chosen
wavelet basis then the library of wavelet bases is applied. The procedure is repeated for each wavelet basis. To select the
best SOTs (and hence, the best wavelet basis) there is the special cost function which considers the SOTs as so-called
coherent structures and shows which of wavelet bases brings the maximum entropy. The results of computer modeling
and comparison with few well-known despeckling procedures have shown the superb quality of the proposed method in
the sense of different criteria as PSNR, SSIM, etc.

In this work we explored a dataset made by more than 100 images acquired by COSMO-SkyMed (CSK) constellation
over the Port-au-Prince (Haiti) metropolitan and surrounding areas that were severely hit by the January 12th, 2010
earthquake. The images were acquired along ascending pass by all the four sensors of the constellation with a mean rate
of 1 acquisition/week. This consistent CSK dataset was fully exploited by using the Persistent Scatterer Interferometry
algorithm SPINUA with the aim of: i) providing a displacement map of the area; ii) assessing the use of CSK and PSI for
ground elevation measurements; iii) exploring the CSK satellite orbital tube in terms of both precision and size. In
particular, significant subsidence phenomena were detected affecting river deltas and coastal areas of the Port-au-Prince
and Carrefour region, as well as very slow slope movements and local ground instabilities. Ground elevation was also
measured on PS targets with resolution of 3m. The density of these measurable targets depends on the ground coverage,
and reaches values higher than 4000 PS/km2 over urban areas, while it drops over vegetated areas or along slopes
affected by layover and shadow. Heights values were compared with LIDAR data at 1m of resolution collected soon
after the 2010 earthquake. Furthermore, by using geocoding procedures and the precise LIDAR data as reference, the
orbital errors affecting CSK records were investigated. The results are in line with other recent studies.

In this paper, the authors have investigated whether the noise whitening procedure developed as a preprocessing step before despeckling of detected images may be useful also in contexts where phase information is exploited. In a preliminary test set, an interferometric pair of COSMO-SkyMed StripMap images, featuring industrial buildings and vegetated areas, has been: 1) focused without Hamming window (aimed at improving the focusing of targets at the cost of introducing a spatial correlation of background noise), starting from raw data. 2) focused with Hamming window, starting from raw data; 3) preprocessed for complex noise whitening, starting from data at point 2). From the complex interferograms, coherence and interferometric phase maps have been calculated for the three cases by means of boxcar filtering. In case 1) coherence is low on vegetation and also suffers from spreading of areas characterized by strong backscattering because of the presence of high sidelobes. In case 2) points targets and buildings in general are much more defined, thanks to the sidelobe suppression achieved by Hamming filtering, but the background coherence is abnormally increased, due to the introduction of a spatial correlation. Case 3) is the most favorable because whitening operation carries out low coherence on vegetation and high coherence on buildings, where the effects of Hamming filtering are retained. An analysis of the phase field reveals that case 3) should be expedited also in terms of phase unwrapping. Thus, the whitening procedure, devised as a blind preprocessing patch of SLC data, with the goal of a better despeckling, is useful also for SAR interferometry, in which the tradeoff, dictated by the coefficient of the Hamming window, between the ideal situations of focused targets and uncorrelated speckle may be relaxed.

A multitemporal algorithm (MLTA) to retrieve soil moisture from radar data, already developed and preliminarily
validated for Sentinel 11, has been modified/updated in order to ingest data provided by the future SMAP (Soil Moisture
Active and Passive) mission. Moreover, the MLTA has been tested using actual EO data at C-band and in situ data
considering a sort of worst case i.e., under well-developed vegetation conditions. The implemented MLT approach
consists of integrating a dense time series of radar backscatter measurements within a multitemporal inversion scheme
based on the Bayesian Maximum A Posteriori (MAP) criterion. The MAP estimator maximizes the probability density
function of the vector of soil parameters (soil moisture and roughness) conditioned to the measurement vector. To correct
the vegetation effects, the water cloud model has been modified in order to better account for the effect of the volume
scattering. Preliminary results have assessed the potential of the algorithm at L-band, whilst the SAR C-band data turned
out to be sensitive to soil moisture even when vegetation was developed.

Frequent and spatially distributed measurements of soil moisture (SMC), at different spatial scales, are advisable for all
applications related to the environmental disciplines, such as climatology, meteorology, hydrology and agriculture.
Satellite sensors operating in the low part of microwave spectrum are very suitable for this purpose, and their signals can
be directly related to the moisture content of the observed surfaces, provided that all the contributions from soil and
vegetation to the measured signal are properly accounted for.
Among the algorithms used for the retrieval of SMC from both active (i.e. Synthetic Aperture Radar, SAR or real aperture
radars) and passive (radiometers) microwave sensors, the artificial neural networks (ANN) represent the best compromise
between accuracy and computation speed. ANN based algorithms have been developed at IFAC, and adapted to several
radar and radiometric satellite sensors, in order to generate SMC products at different spatial resolutions, varying from
hundreds of meters to tens of kilometers.
These algorithms, which use the ANN techniques for inverting theoretical and semi-empirical models, such as Advanced
Integral Equation (AIEM), Oh models, and Radiative transfer Theory (RTT), have been adapted to the C-band acquisitions
from SAR (Envisat/ASAR) and real aperture radar (ASCAT) and to the X-band SAR acquisitions of Cosmo-SkyMed and
TerraSAR-X. Moreover, a specific ANN algorithm has also been implemented for the L-band active and passive
acquisitions of the incoming SMAP mission. The latter satellite will carry onboard simultaneously one radar and one
radiometer operating at the same frequency, but with different spatial resolutions (3 and 40 km, respectively).
Large datasets of co-located satellite acquisitions and direct SMC measurements on several test sites located worldwide
have been used along with simulations derived from forward electromagnetic models for setting up, training and validating
these algorithms. An overall quality assessment of the obtained results in terms of accuracy and computational cost was
carried out, and the main advantages and limitations for an operational use of these algorithms have been evaluated.

The goal of this study was to assess the applicability of medium resolution SAR time-series, in combination with in-situ
point measurements and machine learning, for the estimation of soil moisture content (SMC). One of the main
challenges was the combination of SMC point measurements and satellite data. Due to the high spatial variability of soil
moisture a direct linkage can be inappropriate. Data used in this study were a combination of in-situ data, satellite data
and modelled SMC from the hydrological model GEOtop. To relate the point measurements with the satellite pixel
footprint resolution, a spatial upscaling method was developed. It was found that both temporal and spatial SMC patterns
obtained from various data sources (ASAR WS, GEOtop and meteorological stations) show similar behaviors.
Furthermore, it was possible to increase the absolute accuracy of the estimated SMC through spatial upscaling of the
obtained in-situ data. Introducing information on the temporal behavior of the SAR signal proves to be a promising
method to increase the confidence and accuracy of SMC estimations. Following steps were identified as critical for the
retrieval process: the topographic correction and geocoding of SAR data, the calibration of the meteorological stations
and the spatial upscaling.

The application of Persistent Scatterer Interferometry (PSI) to slope instability monitoring poses challenges related to the
complex kinematics of the phenomenon, as well as to the unfavourable settings of the area affected by landslides, often
occurring on sites of limited extension, characterized by steep topography and variable vegetation cover. New-generation
SAR sensors, such as TerraSAR-X (TSX) thanks to their higher spatial resolution, make PSI applications very promising
for monitoring areas with low density man-made. Nevertheless, the application of techniques still remains problematic or
impossible in rural and mountainous areas. This is the case, for instance, for the Municipality of Carlantino, in Southern
Italy. Both C-band medium resolution SAR data from ESA satellites, and X-band high resolution SAR data from the
TSX satellite, were processed through the PSI algorithm SPINUA. Despite the higher spatial density of PS from TSX,
the landslide body is lacking coherent targets, due to vegetation and variable land cover. To allow stability monitoring, a
network of six CRs was designed and deployed over the landslide test site. Twenty-six TSX stripmap images were
processed by using both PSI and an ad hoc procedure based on double-difference analysis of DInSAR phase values on
the CR pixels, constrained by the accurate CR height measurements provided by DGPS. Despite the residual noise due to
the sub-optimal CR network and the strong atmospheric signal, displacement estimation on the CRs allows to propagate
the PSI results downslope, proving the stability of the landslide area subjected to consolidation works.

SAR systems are recently used to generate robust and projectable information about maritime traffic, ice extent and geohazards. By utilising multiple SAR satellites dynamic information can be derived at variable temporal scales. Therefore acquisition systems and processing techniques become a key issue which is requested to work in a robust and efficient way. This paper will present generalized concepts for a monitoring approach that address unmatched or interferometric acquisitions. Its goal is to show the potential of increasing the acquisition rate but also to illustrate limitations resulting from the specific monitoring schemes and their combination. The paper will visualise practical examples derived from realized studies and projects. Finally we can conclude that an agile multi satellite and multi-mode SAR system, such as COSMO-SkyMed, is well suited to monitor to dynamic phenomena on the earth’s surface. The practicability needs to be discussed in detail case by case related to the real world requirements.

The PSIG procedure is a new approach to Persistent Scatterer Interferometry (PSI), which is implemented in the in-house
PSI chain of the Geomatics Division of the CTTC. The PSIG procedure has been successfully tested over urban, rural
and vegetated areas using X-band SAR data. This paper briefly describes the main steps of the procedure, mainly
focusing on the two key processing steps of the approach. The first one is a selection of Persistent Scatterers (PS)
consisting in a candidate Cousin PS (CPS) selection based on a phase similitude criteria that allows a correct phase
unwrapping and a phase unwrapping consistency check. The second key element is a 2+1D phase unwrapping algorithm,
which consists in a 2D phase unwrapping followed by a 1D phase unwrapping that allows the detection and correction of
unwrapping errors. The results of the CPS selection and the 2+1D phase unwrapping obtained using a stack of 28
TerraSAR-X StripMap images over the metropolitan area of Barcelona are shown.

A Ground-Based Synthetic Aperture Radar (GB-SAR) is nowadays employed in several applications. The processing of
ground-based, space and airborne SAR data relies on the same physical principles. Nevertheless specific algorithms for
the focusing of data acquired by GB-SAR system have been proposed in literature.
In this work the impact of the main focusing methods on the interferometric phase dispersion and on the coherence has
been studied by employing a real dataset obtained by carrying out an experiment. Several acquisitions of a scene with a
corner reflector mounted on a micrometric screw have been made; before some acquisitions the micrometric screw has
been displaced of few millimetres in the Line-of-Sight direction. The images have been first focused by using two
different algorithms and correspondently, two different sets of interferograms have been generated. The mean and
standard deviation of the phase values in correspondence of the corner reflector have been compared to those obtained by
knowing the real displacement of the micrometric screw. The mean phase and its dispersion and the coherence values for
each focusing algorithm have been quantified and both the precision and the accuracy of the interferometic phase
measurements obtained by using the two different focusing methods have been assessed.

Digital Elevation Model (DEM) is a key input for the development of risk management systems. Main limitation of the current available DEM is the low level of resolution. DEMs such as STRM 90m or ASTER are globally available free of charge, but offer limited use, for example, to flood modelers in most geographic areas. TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurement), the first bistatic SAR can fulfil this gap. The mission objective is the generation of a consistent global digital elevation model with an unprecedented accuracy according to the HRTI-3 (High Resolution Terrain Information) specifications. The mission opens a new era in risk assessment. In the framework of ALTAMIRA INFORMATION research activities, the DIAPASON (Differential Interferometric Automated Process Applied to Survey Of Nature) processing chain has been successfully adapted to TanDEM-X CoSSC (Coregistered Slant Range Single Look Complex) data processing. In this study the capability of CoSSC data for DEM generation is investigated. Within the on-going FP7 RASOR project (Rapid Analysis and Spatialisation and Of Risk), the generated DEM are compared with Intermediate DEM derived from the TanDEM-X first global coverage. The results are presented and discussed.

Within the Copernicus programme there is much interest in the ability of remote sensing technology to deliver
operational solutions to many areas of life including environmental management. This paper describes research focused
on the application of Earth Observation for Integrated Coastal Zone Management. The main topic of this research is to
explore to which extent salt marsh vegetation habitats can be identified from polarimetric SAR remotely sensed data.
Multi-frequency, multi-polarimetric SAR images from airborne (S- and X-Band quad-polarimetric from the Astrium
airborne SAR Demonstrator) is used to examine salt marsh habitat classification potential in the Llanrhidian salt marshes
in South Wales, UK. This is achieved by (1) using both supervised and unsupervised classification routines, using
several polarimetric SAR data layers as backscatter intensity, band ratios and polarimetric decomposition products, and
by (2) statistical analysis by regression of these different SAR data layers and botanical parameters acquired from recent
ecological fieldwork.

This work aims at investigating the capability of COSMO-SkyMed® (CSK®) constellation of Synthetic Aperture Radar
(SAR) system to monitor the Leaf Area Index (LAI) of different crops. The experiment was conducted in the Marchfeld
Region, an agricultural Austrian area, and focused on five crop species: sugar beet, soybean, potato, pea and corn. A
linear regression analysis was carried out to assess the sensitivity of CSK® backscattering coefficients to crops changes
base on LAI values. CSK® backscattering coefficients were averaged at a field scale (<σ°dB>) and were compared to the
DEIMOS-1 derived values of estimated LAI. LAI were as well averaged over the corresponding fields (<LAIest>). CSK®
data acquired at three polarizations (HH, VV and VH), four incidence angles (23°, 33°, 40° and 57°) and at different
pixel spacings (2.5 m and 10 m) were tested to assess whether spatial resolution may influence results at a field scale and
to find the best combination of polarizations and CSK® acquisition beams which indicate the highest sensitivity to crop
LAI values. The preliminary results show that sugar beet can be well monitored (r = 0.72 - 0.80) by CSK® by using any
of the polarization acquisition modes, at moderate to shallow incidence angles (33° - 57°). Slightly weaker correlations
were found, at VH polarization only, between CSK® < σ°dB> and <LAIest> for potato (r = 0.65), pea (r = 0.65) and
soybean (r = -0.83). Shallower view incidence angles seem to be preferable to steep ones in most cases. CSK®
backscattering coefficients were no sensitive at all to LAI changes for already developed corn fields.

In this work we address the synergy of optical, SAR (Synthetic Aperture Radar) and topographic data in soil moisture retrieval over an Alpine area. As estimation technique, we consider Gaussian Process Regression (GPR). The test area is located in South Tyrol, Italy where the main land types are meadows and pastures. Time series of ASAR Wide Swath - SAR, optical, topographic and ancillary data (meteorological information and snow cover maps) acquired repetitively in 2010 were examined. Regarding optical data, we used both, daily MODIS reflectances, and daily NDVI, interpolated from the 16-day MODIS composite. Slope, elevation and aspect were extracted from a 2.5 m DEM (Digital Elevation Model) and resampled to 10 m. Daily soil moisture measurements were collected in the three fixed stations (two located in meadows and one located in pasture). The snow maps were used to mask the points covered by snow. The best performance was obtained by adding MODIS band 6 at
1640 nm to SAR and DEM features. The corresponding coefficient of determination, R2, was equal to 0.848, and the root mean square error, RMSE, to 5.4 % Vol. Compared to the case when no optical data were considered, there was an increase of ca. 0.05 in R2 and a decrease in RMSE of ca. 0.7 % Vol. This work showed that the joint use of NDVI or water absorption reflectance with SAR and topographic data can improve the estimation of soil moisture in specific Alpine area and that GPR is an effective method for estimation.

SAR instruments with polarimetric capabilities, high resolution and short revisit time can provide powerful support in oil
spill monitoring and different techniques of analysis have been developed for this purpose [1][2]. An oil film on the sea
surface results in darker areas in SAR images, but careful interpretation is required because dark spots can also be caused
by natural phenomena. In view of the very low backscatter from slicks, the Noise Equivalent Sigma Zero (NESZ) is a
primary sensor parameter to be considered when using a sensor for slick analysis. Among the existing full polarimetric
sensors, the high resolution and very low NESZ values of UAVSAR (L-band) and RADARSAT-2 (C-band) make them
preferable for oil spill analysis compared to the last generation SAR instruments. The Deepwater Horizon disaster that
occurred in the Gulf of Mexico in 2010 represents a unique and extensive test site where large amounts of SAR imagery
and ground validation data are available. By applying the Cloude-Pottier decomposition method to full polarimetric
UAVSAR (L-band) and RADARSAT-2 (C-band), it is possible to extract parameters that describe the scattering
mechanism of the target. By comparing quasi-simultaneous acquisitions and exploiting the different penetration
capabilities of the sensors, we investigate the potential of full polarimetric SAR to discriminate oil on the sea surface
from look-alike phenomena covering the full range of backscattering values down to those at the instrument noise floor.

This paper presents a novel algorithm for wake detection in Synthetic Aperture Radar images of the sea. The algorithm
has been conceived as part of a ship traffic monitoring system, in charge of ship detection validation and to estimate ship
route features, such as heading and ground speed. In addition, it has been intended to be adequate for inclusion in an
automatic procedure without human operator supervision. The algorithm exploits the Radon transform to identify the
images ship wake on the basis of the well known theoretical characteristics of the wakes’ geometry and components, that
are the turbulent wake, the narrow-V wakes, and the Kelvin arms, as well as the typical appearance of such components
in Synthetic Aperture Radar images of the sea as bright or dark linear feature. Examples of application to high-resolution
X-band Synthetic Aperture Radar products (COSMOSkymed and TerraSAR-X) are reported, both for wake detection
and ship route estimation, showing the achieved quality and reliability of wake detection, adequacy to automatic
procedures, as well as speed measure accuracy.

Ka-band RADAR frequency range has not yet been used for Synthetic Aperture Radar (SAR) from space so far,
although this technology may lead to important applications for the next generation of SAR space sensors. Therefore,
feasibility studies regarding a Ka-band SAR instrument have been started [1][2], for the next generation of SAR space
sensors. In spite of this, the lack of trusted references on backscatter at Ka-band revealed to be the main limitation for the
investigation of the potentialities of this technology.
In the framework of the ESA project “Ka-band SAR backscatter analysis in support of future applications”, this paper is
aimed at the study of wave interaction at Ka-band for a wide range of targets in order to define a set of well calibrated
and reliable Ka-band backscatter coefficients for different kinds of targets. We propose several examples of backscatter
data resulting from a critical survey of available datasets at Ka-band, focusing on the most interesting cases and
addressing both correspondences and differences. The reliability of the results will be assessed via a preliminary
comparison with ElectroMagnetic (EM) theoretical models. Furthermore, in support of future technological applications,
we have designed a prototypal software acting as a “library” of earth surface radar response. In our intention, the output
of the study shall contribute to answer to the need of a trustworthy Ka-Band backscatter reference. It will be of great
value for future technological applications, such as support to instrument analysis, design and requirements’ definition
(e.g.: Signal to Noise Ratio, Noise Equivalent Sigma Zero).

An interferometric performance analysis for repeat-pass geosynchronous circular SAR (GEOCSAR) is presented. The
analysis mainly includes the errors caused by the following sources: radar thermal noise, spatial baseline decorrelation,
images’ misregistration and the atmospheric effects. For circular SAR (CSAR) imaging on the geosynchronous orbit, the
altitude is very high, the atmospheric effect is severe and the high sidelobe is existed in the focused GEOCSAR signal,
the characteristics of the various error sources of GEOCSAR interferometry will behave differently from the
conventional interferometric SAR.

As the introducing first part of this paper, the data set of Christchurch, New Zealand, is outlined with regard to its purpose: the detection of earthquake damages. The aim is to produce simulated SAR images that are realistic enough to function successfully as pre-event images in a change detection effort. To this end, some modifications to the input 3D city model are introduced and discussed. This includes the use of a GIS map, for a realistic modelling of the radiometric variety, and the insertion of high vegetation to the model, so as to achieve a realistic occlusion of building corners. A detailed description of the impact, these modifications have on the simulation, is given and a comparison between the simulations and corresponding real data is drawn.

SAR Tomography is the extension of the conventional interferometric radar signal processing, extended in the
height dimension. In order to improve the vertical resolution with respect to the classical Fourier methods, high
resolution approaches, based on the Convex Optimization (CVX), has been implemented. This methods recast in the
Compressed Sensing (CS) framework that optimize tomographic smooth profiles via atomic decomposition, in order
to obtain sparsity. The optimum solution has been estimated by Interior Point Methods (IPM). The problem for such
kind of signal processing is that the tomographic phase information may be suppressed and only the optimized
energy information is available. In this paper we propose a method in order to estimate an optimized spectra and
phase information projecting each vector components of each tomographic resolution cell spanned in the real and
the imaginary component. The tomographic solutions has been performed by processing multi-baseline SAR
datasets, in a full polarimetric mode, acquired by a portable small Continuous Wave (CW) radar in the X band.

Defence Research and Development Canada has been investigating 3-D through wall synthetic aperture radar (SAR) imaging from an experimental L-band through-wall SAR prototype. Tools and algorithms for 3-D visualization are being developed to exploit the resulting imagery. In this paper, a comprehensive study of the characteristics of human target signatures in free space and behind two different wall structures is presented using 3-D SAR data. The aim of this investigation is to gain a better appreciation of the signatures of targets when placed behind different wall materials. An analysis of the human target signature in different poses is provided. There was very close agreement between the measured physical dimensions of the targets and those obtained from the strong returns in the SAR imagery. Viewing of the SAR data as 2-D slices provides a qualitative means of discriminating between different target signatures. A more useful approach to discrimination is to quantify these differences. The next phase of this investigation will look at different quantitative features as potential discriminants.

A study was conducted for developing an automatic sub-pixel matching methodology and applying on the imageries of
one of the high-resolution SAR satellites, TerraSAR-X. The results indicated the accuracy of about 0.2 m in X direction,
and better than 0.1 m in Y direction by comparing with the referenced GNSS observation data. This study was aimed to
show the accuracy and feature of the displacement depending on the land cover types of the objects of the selected
matching points using the three pairs of TerraSAR-X images of Tohoku region acquired pre- and post-earthquake in
2011. The developed methodology is focused on the spatial texture around the point, and there is some possibility that
different kinds of objects except man-made buildings are utilized to calculate the displacement. Selected point of each
sub-area was classified into several objects firstly, and the correlation coefficient and the amplitude for the selected
points were analyzed subsequently. Finally the statistical analysis was conducted, and showed the errors of the
displacement quantitatively for each object. This paper describes the knowledge for the applied methodology to highresolution
SAR satellite imageries in detail, and also implies the key points for the improvement.

We present an investigation of surface deformation using Differential SAR Interferometry (DInSAR) time-series carried
out in an active open pit iron mine, the N5W, located in the Carajás Mineral Province (Brazilian Amazon region), using
33 TerraSAR-X (TSX-1) scenes. This mine has presented a historical of instability and surface monitoring measurements
over sectors of the mine (pit walls) have been done based on ground based radar. Two complementary approaches were
used: the standard DInSAR configuration, as an early warning of the slope instability conditions, and the DInSAR timeseries
analysis. In order to decrease the topographic phase error a high resolution DEM was generated based on a stereo
GeoEye-1 pair. Despite the fact that a DinSAR contains atmospheric and topographic phase artifacts and noise, it was
possible to detect deformation in some interferometric pairs, covering pit benches, road ramps and waste piles. The timeseries
analysis was performed using the 31 interferometric pairs, which were selected based on the highest mean
coherence of a stack of 107 interferograms, presenting less phase unwrapping errors. The time-series deformation was
retrieved by the Least-Squares (LS) solution using an extension of the Singular Value Decomposition (SVD), with a set
of additional weighted constrain on the acceleration deformation. The atmospheric phase artifacts were filtered in the
space–time domain and the DEM height errors were estimated based on the normal baseline diversity. The DInSAR
time-series investigation showed good results for monitoring surface displacement in the N5W mine located in a tropical
rainforest environment, providing very useful information about the ground movement for alarm, planning and risk
assessment.

In this paper, a novel three-dimensional imaging algorithm of downward-looking linear array SAR is presented. To improve the resolution, multiple signal classification (MUSIC) algorithm has been used. However, since the scattering centers are always correlated in real SAR system, the estimated covariance matrix becomes singular. To address the problem, a three-dimensional spatial smoothing method is proposed in this paper to restore the singular covariance matrix to a full-rank one. The three-dimensional signal matrix can be divided into a set of orthogonal three-dimensional subspaces. The main idea of the method is based on extracting the array correlation matrix as the average of all correlation matrices from the subspaces. In addition, the spectral height of the peaks contains no information with regard to the scattering intensity of the different scattering centers, thus it is difficulty to reconstruct the backscattering information. The least square strategy is used to estimate the amplitude of the scattering center in this paper. The above results of the theoretical analysis are verified by 3-D scene simulations and experiments on real data.

Synthetic aperture radar tomography (TomoSAR) is typically used to retrieve elevation, deformation, and other key
information by separating scatters of the same slant range in multiple baseline SAR images. In this paper, we investigate
two kinds of ambiguities for TomoSAR. Rank-1 ambiguity, as the first one we concerned, is due to the baseline
distribution of the SAR image dataset which makes the steering matrix out of full rank. It will result in false alarms
appearing in a permanent distance. However, an example using the TomoSAR imaging parameters shows this ambiguity
makes no sense in most cases. The second ambiguity refers to the coherence of scatters contained in one pixel. In
simulation experiment, the coherence will enhance the side lobes of the spectrum, even make the real peaks fused.

Ship detection is a significant application of maritime monitoring and security. To fully explore the potential of wide
coverage of synthetic aperture radar (SAR) image, the ScanSAR Wide image for ship detection is investigated in this
paper. The Radarsat-2 ScanSAR Wide mode image is used as the image source due to its huge coverage and constant
false alarm rate (CFAR) with Gamma distribution is selected as the core detector. Two problems of ScanSAR ship
detection, the unbalanced phenomenon and false alarms of islands, are investigated and solved by a compensation step
and Hessian matrix respectively. For more aspects, the detector also concerns the polarization channel selection and
distribution fitting. Finally, a whole flow chart of ScanSAR ship detection is presented. As test cases, the experimental
image is used to show the efficiency of our method.

Excessive pumping of groundwater in the Metro Manila district, the Philippines, has occurred huge land subsidence. The
purpose of this study is to investigate the distribution of spatial and temporal change on the earth surface in this area. We
measured long-term ground subsidence by InSAR using JERS-1/SAR, ENVISAT/ASAR, Fine-beam, polarimetry and
ScanSAR mode of ALOS/PALSAR, and TerraSAR-X data. As a result, we detected apparent subsidence and uplift
patterns at eight locations. They have been found to correlate with up-down motion of groundwater level. The largest
amount of ground subsidence was measured approximately 600 mm over 6 years (100mm/year).

In studying image formation methods of the spaceborne synthetic aperture radar (SAR), we utilize its modeling and
simulation (M&S) to generate its realistic simulated rawdata. Especially, for the spaceborne spotlight SAR, we perform
M&S that reflects its real characteristics, and get rawdata that are almost identical to one acquired by the real SAR
sensor.
Particularly, operations of the spaceborne spotlight SAR are simulated based on models of its dynamics and geometry
related to timeline, orbital state vector, antenna beam pattern, azimuth beam steering, and etc. In addition, the target
observation of it is modeled as evaluating observation angles related to point targets within the acquisition time. Finally,
based on the received echo signal model, rawdata are simulated for point targets taking into account its real operation.
For the high resolution SAR image formation, simulated rawdata are focused with the extended chirp scaling algorithm.
Especially, its range cell migration (RCM) factor is the key one for the exact range cell migration correction. In order to
do it accurately, the Doppler frequency and the effective velocity have to be calculated correctly for all range sample
bins. For precise processing, we suggest the method to analyze them using orbital state vectors and scene coordinates
based on two way slant range model.
In experiments, system parameters and imaging scenarios to simulate rawdata acquisition of the spaceborne spotlight
SAR system are defined. The processing results for realistic simulated rawdata of it are presented to evaluate the
performance and the effectiveness of proposed methods. Its results show that suggested methods are applicable to form
the high resolution spaceborne spotlight SAR image.

The frequency and impact of natural disasters worldwide is constantly highlighting the need for quick and appropriate
decisions from civil protection, always supported by the increasing availability of higher resolution, better accuracy,
better revisit and response time data. With COSMO-SkyMed Italy has offered, and still offers today, an efficient
response to actual needs of environment management during a high number of real emergency events, such as
earthquakes. COSMO-SkyMed (Constellation of Small Satellites for Mediterranean basin observation) is the largest
investment of the Italian Space Agency (ASI) for Earth Observation (EO), completely commissioned and funded by the
Italian Ministry of Research and the Ministry of Defense. It is a Dual-Use (Civilian and Defense) system aimed at
establishing a global service supplying provision of data and services relevant to a wide range of applications, such as
Risk and Emergency Management. The COSMO-SkyMed constellation is providing a significant contribution to
Emergency Management providing timely and accurate radar images used in a wide variety of applications such as
earthquake damage assessment. In this paper the analysis related to the application of COSMO-SkyMed data supporting
emergency response operations in case of earthquakes as well as the description of some real use cases occurred in the
last years will be presented.

The continuous monitoring of ground deformation and structural movement has become an important task in
engineering. MetaSensing introduces a novel sensor system, the Fast Ground Based Synthetic Aperture Radar
(FastGBSAR), based on innovative technologies that have already been successfully applied to airborne SAR
applications. The FastGBSAR allows the remote sensing of deformations of a slope or infrastructure from up to a
distance of 4 km.
The FastGBSAR can be setup in two different configurations: in Real Aperture Radar (RAR) mode it is capable of
accurately measuring displacements along a linear range profile, ideal for monitoring vibrations of structures like bridges
and towers (displacement accuracy up to 0.01 mm). Modal parameters can be determined within half an hour.
Alternatively, in Synthetic Aperture Radar (SAR) configuration it produces two-dimensional displacement images with
an acquisition time of less than 5 seconds, ideal for monitoring areal structures like dams, landslides and open pit mines
(displacement accuracy up to 0.1 mm).
The MetaSensing FastGBSAR is the first ground based SAR instrument on the market able to produce two-dimensional
deformation maps with this high acquisition rate. By that, deformation time series with a high temporal and spatial
resolution can be generated, giving detailed information useful to determine the deformation mechanisms involved and
eventually to predict an incoming failure.
The system is fully portable and can be quickly installed on bedrock or a basement. The data acquisition and processing
can be fully automated leading to a low effort in instrument operation and maintenance. Due to the short acquisition time
of FastGBSAR, the coherence between two acquisitions is very high and the phase unwrapping is simplified enormously.
This yields a high density of resolution cells with good quality and high reliability of the acquired deformations. The
deformation maps can directly be used as input into an Early Warning system, to determine the state and danger of a
slope or structure.
In this paper, the technical principles of the instrument are described and case studies of different monitoring tasks are
presented.

Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality
parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In
this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the
region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to
improve the regression models. These models are established and developed to estimate six common concerned water
quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence
Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast,
correlation, energy, homogeneity, entropy and variance.
For each predicted model, an accuracy value is computed from the probability value given by the regression analysis
model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and
test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the
fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from
segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between
the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture
analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.

The problems of simulation of bistatic SAR raw data and focusing are studied. A discrete target simulator is described.
The simulator introduces the scene topography and compute the integration time of general bistatic configurations
providing a means to derived maps of the range and azimuth spatial resolutions. The problem of focusing of bistatic SAR
data acquired in a translational-invariant bistatic configuration is studied by deriving the bistatic Point Target Reference
spectrum and presenting an analytical solution for its stationary points.

In the context of recent advances in InSAR processing techniques to retrieve higher persistent scatterer and coherent
target densities over unfavourable land cover classes, this study tests the Intermittent Small Baseline Subset (ISBAS)
approach to update the landslide inventory around the town of Piana degli Albanesi (Italy), an area where only 2% of the
land appears suitable to generate radar scatterers based on a pre-survey feasibility assessment. ISBAS processing of 38
ascending mode and 36 descending mode COSMO-SkyMed StripMap HIMAGE SAR scenes at 3m resolution allows
identification of ~726,000 and ~893,000 coherent and intermittently coherent pixels for the ascending and descending
data stacks respectively. Observed improvements in the number of ISBAS solutions for the ascending mode are greater
than 40 times compared to the conventional SBAS approach, not only for urban and rocky terrains, but also rural and
vegetated land covers. Line of sight ground motion rates range between -6.4 and +5.5 mm/yr in 2008-2011, although the
majority of the processed area shows general stability, with average rates of -0.6 mm/yr in the ascending and -0.1 mm/yr
in the descending mode results. Interpretation of the ISBAS deformation rates, integrated with targeted field surveys and
aerial photo-interpretation, provides a new and more complete picture of landslide distribution, state of activity and
intensity in the test area, and allows depiction of very slow and extremely slow landslide processes even in areas difficult
to access, with unprecedented coverage of results.

The availability of the data provided by present and future constellations of Synthetic Aperture Radar (SAR) sensors and
the development of reliable flood mapping algorithms allows producing frequent flood maps characterized by high
spatial resolution. Progresses have been also achieved in flood modeling, so that a joint use of SAR-derived and modelderived
inundation maps seems to be very promising. This paper presents the major outcomes of a combined use of a
multi-temporal series of COSMO-SkyMed observations and of a hydrodynamic model, accomplished within the
framework of an activity aiming at the interpretation of the dynamics of the flood that hit Albania in January 2010. By
calibrating the model with the COSMO-SkyMed derived maps, a number of products such as water depths, and flow
directions were generated. Results show a good agreement between SAR-derived and model-derived flood extents.
Moreover, the maximum water depths were found in the areas where floodwater was present for the longest period of
time, according to COSMO-SkyMed observations.